Using R to Visualize 3M Stock Performance

This is a record of my analysis on 3M stock. I put the R code and its outputs below. The data in CSV sheet is from 3M’s Investor Relations web pages. For the R code file and the CSV file, you can download here.

Play_data<-read.csv("mmm.csv")
library(tidyverse)
colnames(Play_data)<-c("Year","EPS","Dividend","Payout","Sales")

library(reshape2)
d <- melt(Play_data, id.vars="Year")

d %>% filter(variable=="Sales") %>%ggplot(aes(x =as.factor(Year) , y = value,,label=value))+geom_bar(stat ="identity", position="dodge", color="dodgerblue1", fill="dodgerblue1") + theme_classic() +
  labs( x = "Year", y = "Sales (billions)")+geom_text(vjust=1,color="white")

d %>% filter(variable=="EPS" | variable=="Dividend") %>%ggplot(aes(x =as.factor(Year) , y = value , fill = as.factor(variable)))+
  geom_bar(stat = "identity",position="dodge")+theme_classic()+labs( x = "Year", y = "Dollars")+guides(fill=guide_legend(title=""))+
  theme(legend.position = c(0.2, 0.9))

percent <- function(x, digits = 0, format = "f", ...) {
  paste0(formatC(100 * x, format = format, digits = digits, ...), "%")
}

d %>% filter(variable=="Payout") %>% mutate(label = percent(value)) %>%ggplot(aes(x =as.factor(Year) , y = value,group = 1,label=label))+
  geom_point(color="darkturquoise",size=1)+geom_line(color="darkturquoise")+theme_classic() + labs( x = "Year", y = "Payout Ratio")+ scale_y_continuous (labels = scales::percent)+ geom_text(vjust=0,color="darkturquoise")

percent <- function(x, digits = 1, format = "f", ...) {
  paste0(formatC(100 * x, format = format, digits = digits, ...), "%")
}

library(ggrepel)

dd<-d %>% filter(variable=="Dividend") %>%  mutate(p_increased = (value - lag(value))/lag(value)) %>% mutate(label = percent((value - lag(value))/lag(value))) 

dd2<-d %>% filter(variable=="EPS") %>%  mutate(p_increased = (value - lag(value))/lag(value)) %>% mutate(label = percent((value - lag(value))/lag(value))) 

rbind(dd,dd2)%>%ggplot (aes(x =as.factor(Year) , y = p_increased,group=variable,label=label))+ geom_line(aes(color=variable))+
  geom_point(aes(color=variable))+theme_classic()+labs( x = "Year", y = "YOY Growth")+ scale_y_continuous(labels = scales::percent)+ geom_text_repel (aes(color=variable),size = 3, force = 3)+ guides(fill=guide_legend(title=""))+
  theme(legend.position = c(0.2, 0.9))

In the following, I assume that 3M has a YOY growth of 2% for both the sales and dividends. I want to see how they look like in 10 years with such growth rate. As you can see, the pay out ratio is pretty high, and it is alarming to investors.

Project_div<-as.data.frame(seq(2019,2029,by=1))
colnames(Project_div)<-"Year"

geomSeq <- function(start,ratio,begin,end){
  begin=begin-1
  end=end-1
  start*ratio**(begin:end)}

Dividends_p<-as.data.frame(geomSeq(5.76,1.02,1,11))
colnames(Dividends_p)<-"Dividends" Project_new<-cbind (Project_div,Dividends_p)

EPS_p<-as.data.frame(geomSeq(7.81,1.02,1,11))
colnames (EPS_p)<-"EPS" Project_new<-cbind(Project_new,EPS_p)

Project_new_new<- melt(Project_new, id.vars="Year")
Project_new_new %>% ggplot(aes(x =as.factor(Year) , y = value , fill = as.factor(variable)))+ geom_bar(stat = "identity",position="dodge")+theme_classic()+labs( x = "Year", y = "Dollars") + guides(fill=guide_legend(title=""))+ theme(legend.position = c(0.2, 1))

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